Method for precise genetic diagnosis

ABSTRACT

Methods and apparatuses for selecting and arranging clinically relevant chromosomal loci allow an exemplary diagnostic array to simultaneously test for numerous genetic alterations that occur in many different parts of the human genome. Clinically irrelevant or ineffective loci are eliminated. One implementation increases reliability and accuracy by dividing the base-pair sequence of each chromosomal locus into segments and then assigning nucleic acid clones for comparative genomic hybridization to each different segment. The segments may overlap for increased resolution and control. Clones representing segments that are adjacent on a native chromosome are placed in non-adjacent target areas of the array to avoid interfering hybridization reactions. Arrangement motifs within an array may be redundantly repeated for high availability and increased reliability and accuracy of results. Techniques, hardware, software, logic engines, loci collections, and diagnostic arrays are described.

RELATED APPLICATIONS

This is a divisional application as restricted by the USPTO and therebyclaims priority under 35 U.S.C. §119(e) to U.S. patent application Ser.No. 11/057,088 to Shaffer and Bejjani, entitled, “Methods andApparatuses for Achieving Precision Diagnoses,” filed Feb. 11, 2005,which in turn claims priority to U.S. Provisional Patent Application No.60/576,890 to Shaffer and Bejjani, filed Jun. 3, 2004, and to U.S.Provisional Patent Application No. 60/544,877 to Shaffer and Bejjani,filed Feb. 13, 2004. These three patent applications are incorporatedherein by reference in their entireties.

TECHNICAL FIELD

The subject matter relates generally to molecular biology and morespecifically to a method for precise genetic diagnosis.

BACKGROUND

Chromosome analysis is an important component in diagnosing congenitalanomalies that cause physical and mental developmental delay.Cytogenetic imbalance results in DNA copy-number changes and alterationin gene dosage in the altered chromosomal segment(s). These changes mayresult in abnormal clinical phenotypes. Such chromosomal aberrations areconventionally detected by a variety of methods, each with distinctadvantages and disadvantages. Routine cytogenetic analysis by GTGbanding can achieve a resolution sufficient to detect aneuploidy andstructural rearrangements of base-pair sequences greater than fivemegabases (Mb) but cannot reliably identify abnormalities less than fiveMb.

More subtle genetic alterations or those involving regions that aredifficult to visualize may be undetectable by conventional cytogenetictechniques (e.g., these include most microdeletion syndromes andexchanges of similarly banded segments that lead to cryptictranslocations). Fluorescence in situ hybridization (FISH) was developedto probe individual chromosomal loci at a resolution equal to the sizeof the probe (e.g., 35-200 kilobases (Kb)). Only a few loci may beexamined at a time, however, and FISH can usually only be performed in alimited manner based on phenotype. Thus, single locus FISH is not anappropriate screening tool for the analysis of more than a few loci at atime.

Additional molecular cytogenetic techniques were developed to overcomethese limitations. Comparative genomic hybridization (CGH) was developedto identify chromosomal imbalance without the need for phenotypicinformation, circumventing multiple FISH experiments. CGH providesgenome-wide screening of genetic sequence alterations by comparingdifferentially labeled test and control samples of genomic DNA. Theresolution of the technique, however, is still limited to approximately5-10 Mb because metaphase chromosomes are used as the targets foranalysis.

To substantially increase the resolution, CGH-based microarrays forperforming “array CGH” were developed. Array CGH is a high-resolution,comprehensive method for detecting both genome-wide andchromosome-specific copy-number imbalances. Array CGH typically useslarge-insert clones (such as bacterial artificial chromosomes, “BACs”)as the target for analysis rather than metaphase chromosomes. As aconsequence, the resolution of the array is limited only by the size ofthe insert used and the physical distance in the human genome betweenclones that are selected for the array.

CGH microarrays have been successfully constructed to test many parts ofthe human genome. In 2001, a whole-genome array was constructed usingapproximately 2400 BAC clones to scan for genome-wide copy-numberalterations. An array covering some of the telomeric regions of thehuman genome has also been developed. Individual chromosomal regionshave also provided good targets for array CGH. For example, in 2003 amicroarray was designed to cover much of the most distal 10.5 Mb ofchromosome location 1p36 to study subjects with monosomy 1p36. In 2003,an array was constructed based on chromosome 18 to study patients withcongenital anal atresia. Microarrays have also been developed to testparts of chromosomes 20 and 22.

As shown in FIG. 1, conventional CGH microarrays 100 constructed forresearch purposes are designed to screen chromosomal regions or theentire genome for chromosomal segment gains or segment losses withimproved resolution over earlier techniques. For many reasons, however,most of these are not appropriate or relevant for use in clinicalgenetic diagnosis. First, most conventional BACs used in thesemicroarrays have been culled from BAC databases without prior externalverification of the exact locations (“loci”) that they map to (“cover”)on a chromosome 102. Second, these databases rarely provide notice thatsome of the BACs map to multiple loci, even on entirely differentchromosomes 104. Third, many of the loci that are covered by a singleclone may show dosage variation due to the inherent technicalvariability of the procedures involved 106. Fourth, the conventional CGHmicroarray 100 may identify alterations in regions of the genome that donot have established clinical relevance 108. Thus, such conventional“whole genome” arrays are likely to generate data that are difficult tointerpret or that are inaccurate in that they present multiple falsepositive results 110. That is, alterations in regions of the genome thatdo not have established clinical relevance are impossible or, at thevery least, expensive to interpret and/or verify in a clinical setting112.

In a clinical setting, a conventional whole-genome approach to array CGHmay cause erroneous test results that result from undesirablepolymorphisms, which are usually abundantly represented in thisapproach. Data from sub-telomere FISH analysis, for example, reveal manytelomeric alterations that possess no clinical significance.

It is estimated that about 35% of clones that are currently availablefrom the public and private databases either map to the wrong location,map to more than one location in the genome, represent polymorphic areasof the genome, or contain repetitive sequences that may interfere withhybridization. Using random clones from the databases would result in aclinical test that has more than a 35% probability of error and that isof dubious utility. Thus, “whole genome arrays” arrays are notappropriate for clinical applications. The adoption of such “wholegenome” arrays for use in clinical diagnostics may be unwise, not onlyleading to many false positive diagnoses that necessitate expensivefollow-up confirmatory tests by FISH or other methods (e.g., 112); butalso additional blood draws from unaffected relatives of the patient todetermine possible segregation of genetic deletions, duplications, orpolymorphisms; not to mention unnecessary anxiety for the family of aperson being tested. In the “whole genome” approach, hybridizationresults for single clones that show dosage difference require carefulexamination and each clinical case may require all the time and expenseof a mini-research project. Thus, genome-wide “dense” arrays that areconventionally available for research use are not appropriate, relevant,or efficient in a clinical setting. There exists a need for a clinicallyuseful diagnostic array that provides reliability, that accuratelydetects chromosome abnormalities assayed, and that providesinterpretable results with an acceptable degree of precision. Further,there exists a need for methods of precision genetic diagnosis thatprovide clinical confidence by interrogating clinically relevant partsof the genome rather than the clinically irrelevant parts.

SUMMARY

The subject matter described herein can be used in various fields togreatly improve the accuracy and reliability of nucleic acid analyses,chromosome mapping, and genetic testing of suspected genetic conditions.In one implementation, aspects of the subject matter are incorporatedinto the construction of a diagnostic array (“array”), such as atemporal array, or a spatial array of tests used, for example, incomparative genomic hybridization (CGH) microarrays. An exemplaryhigh-availability diagnostic array for testing chromosomal lociassociated with human disease and constructed according to aspects ofthe subject matter may use one or more exemplary features, including:selective screening of genetic loci, reliable coverage of the selectedloci, strategic placement of control reference clones, strategicnonrandom distribution of the clones on the microarray, and/or redundantsub-arrays for comparison and dependability.

The subject matter allows error-resistant and high-availability testingof nucleic acid sequence alterations, such as genetic sequence andbase-pair alterations, deletion or duplication of genetic sequence (eachloosely referred to herein as “genetic alterations”) that may representanomalies associated with a disease. In the case of an exemplary CGHmicroarray implementation, clinically relevant chromosomal loci arecarefully selected for their diagnostic efficacy, and the overallbase-pair sequence of each chromosomal locus of interest is parsed ordisassembled into multiple contiguous and/or overlapping segments. Eachsegment—as represented by a nucleic acid clone or synthesizedoligonucleotide—is isolated into a reliable individual test area targeton the microarray, free from the hybridization influences of adjacentsequences that occur on a native chromosome.

Clones representing each individual segment may be included many timesand in different positions in different sub-arrays of an exemplaryarray. When a test is complete, redundant occurrences of an individualsegment test are compared with each other, and the test results of thesegments are logically reassembled back into a combined test result forthe overall base-pair sequence of the chromosomal locus of interest.Because the testing of each chromosomal locus is typically broken upinto multiple segments for isolated and reliable testing; because themultiple segments are typically selected to overlap each other; andbecause each segment is tested redundantly; an exemplary diagnosticarray achieves unprecedented diagnostic resolution, precision, andreliability.

Loci to be included in an exemplary array are screened from the outsetfor their diagnostic usefulness and efficacy, and only clones thatuniquely and reliably map to these loci are allowed in an exemplaryarray, thus assuring clinically relevant and reliable test results. Inother words, loci from “deadwood” parts of the genome are excluded frominclusion and in addition, dependable clones are substituted forundependable ones.

Although an exemplary array limits genetic testing to only chromosomalloci and related regions that provide clinically useful information, anexemplary microarray is comprehensive because chromosomal loci are drawnfrom clinically relevant regions across the entire human genome,including the telomeric and pericentromeric regions. In other words, inone implementation, an exemplary diagnostic array comprises a verycomprehensive battery of diverse tests that usually have to be performedseparately at great cost. Moreover, an exemplary microarray providesunprecedented accuracy and reliability for diagnosing myriad geneticalterations—in one single test.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a flowchart describing problems encountered with “wholegenome” comparative genomic hybridization arrays.

FIG. 2 is a block diagram of an exemplary system for achieving precisiongenetic diagnoses.

FIG. 3 is a graphic representation of an exemplary division of aclinically relevant chromosomal locus into overlapping segments.

FIG. 4 is a graphic representation of an exemplary diagnostic array thatuses segment isolation.

FIG. 5 is a graphic representation of an exemplary method fordistributing segments of a clinically relevant chromosomal locus on anexemplary diagnostic array.

FIG. 6 is a graphic representation of an exemplary method forcompressing an exemplary array by mixing targets for more than onechromosomal location.

FIG. 7 is a block diagram of an exemplary array engine.

FIG. 8 is a block diagram of an exemplary diagnostics engine.

FIG. 9 is a flow diagram of an exemplary method of selecting chromosomalloci.

FIG. 10 is a flow diagram of an exemplary method of distributing clonesin an exemplary array.

FIG. 11 is a flow diagram of an exemplary method of adding flankingcontrols to clinically relevant chromosomal loci on an array.

FIG. 12 is a flow diagram of an exemplary method of replicating anarrangement motif for chromosomal loci on an array in inverse proportionto a determined diagnostic efficacy of the motif.

DETAILED DESCRIPTION Overview

The subject matter described herein can be used in various fields togreatly improve the accuracy and reliability of nucleic acid analyses,chromosome mapping, and genetic testing, e.g., for diagnosing geneticdiseases and cancer. In an implementation that uses a diagnostic array(hereafter, “array”), such as a microarray used for comparative genomichybridization (CGH), a comprehensive battery of clinically relevantchromosomal loci are carefully selected and screened to providestringent diagnostic efficacy. Selected loci are included on anexemplary array. Significantly, clinically irrelevant chromosomalloci—vast portions of the human genome that are irrelevant for makingdiagnoses—are carefully eliminated from being candidates for positionson an exemplary array. These latter inefficacious parts of the genomenot only have no utility for providing clinically useful information,but actually impede accurate and efficient diagnoses in many ways.

The overall genetic code sequence (“base-pair sequence”) of eachclinically relevant chromosomal locus selected for an array may beparsed or disassembled into multiple contiguous and/or overlappingsegments. Each segment—as represented by a nucleic acid clone orsynthesized oligonucleotide—is isolated into a reliable individual testarea (“target”) on an exemplary array, free from interfering influences(on hybridization) of clones that represent adjacent sequences thatoccur on a native chromosome.

A clone representing an individual segment of the base-pair sequence ofa chromosomal locus may be included multiple times and in differentpositions within different sub-arrays of an exemplary array.

When a patient's chromosomal material is tested against the exemplaryarray, redundant occurrences of a given individual segment test arecompared with each other, and test results of the multiple segments of alocus are collated, that is, logically reassembled back into a singlecombined test result for the overall base-pair sequence of the locus.

In one implementation shown in FIG. 2, aspects of the subject matter areincorporated by an array engine 200 into the construction of ahigh-availability array 202. An exemplary array 202 undergoes testconditions 204 using chromosomal loci selected to test for disease andthe resulting clinically reliable information can be logicallyprocessed, for example, by an exemplary diagnostic engine 206 in orderto support very precise diagnoses.

By simultaneously testing clinically relevant chromosomal locistrategically selected from across the entire human genome, includingthe telomeric and pericentromeric regions of chromosomes, an exemplaryarray 202 provides for convenience, cost savings, and diagnosticefficacy.

FIG. 3 shows a chromosomal locus 300 that possesses a base-pair sequence304 located on a chromosome 302. The base-pair sequence 304 of thislocus 300 (and each locus) to be included for testing in or on anexemplary array 202 may be divided into two or more “layers” of segments306, which are also illustrated as segment lines. Nucleic acid clones oralternatively, synthesized oligonucleotides, are assigned to representthe segments 306 of each locus 300. The clones now representing thebase-pair sequence 304 of respective segments 306 are strategicallypositioned in individual targets of an exemplary array 202 in a mannerthat avoids interaction and interpretive errors between adjacentsegments that neighbor each other (e.g., 308 and 310) on the nativechromosome 302.

In one implementation, overlapping segments, such as those shown in FIG.3, can also be used for increased test resolution and certainty ofdiagnosis. In response to a test 204, the test results for eachoverlapping segment of a chromosomal locus 300 are collated into asingle combined test result for the overall base-pair sequence 304 ofeach locus 300, e.g., by an exemplary diagnostics engine 206.

Not only are the chromosomal loci carefully selected, but theaforementioned nucleic acid clones (or synthesized oligonucleotides)that are to represent the segments 306 comprising each locus 300 arecarefully selected and screened (or synthesized) for faithful, accurate,and reliable mapping to their respective segments, as will be discussedmore fully below.

As shown in FIG. 4, in one implementation of an exemplary array 202,copies of clones assigned to a segment 308 of a chromosomal locus 300may be placed into targets in multiple sub-arrays (e.g., 400, 402) toprovide reliability and comparison. Moreover, groups of sub-arrays, suchas an example four block sub-array 404, may be redundantly repeated inan exemplary array 202. On a larger scale, an exemplary array 202consisting of redundantly repeated sub-arrays (e.g., 400, 402) mayitself be redundantly repeated so that arrangement motif of the smallestsub-arrays are redundantly repeated on multiple larger scales. Theamount of redundancy to be imparted to an array may be related to adiagnostic efficacy of part of the array, as discussed more fully belowwith respect to FIG. 11.

Control reference targets may be added to an array 202 for comparisonwith the individual target areas for testing a segment of a chromosomaldiagnostic locus. Multiple clones flanking the chromosomal diagnosticlocus (“flanking clones”) may be selected and distributed on the array202. In one implementation, the flanking clones are placed in adeliberate manner to separate them physically on the array if they arecontiguous in the genome. These controls typically remain unaltereddespite alteration in a diagnostic target of interest. Thus, theflanking controls provide a reliable reference for comparing theintensity of fluorescence signals across targets that are adjacent onthe chromosome but far apart on an array 202.

FIG. 5 shows an exemplary clone distribution 500, in which clonesrepresenting the segments 306 of one or more chromosomal loci 502 arestrategically positioned in targets across an exemplary array 202 toavoid interaction between clones representing adjacent segments on thenative chromosome 302.

In one implementation, a locus consisting of, for example, segments 1-3(in FIG. 5) undergoes distribution of clones representing the segmentsin multiple sub-arrays of the exemplary array 202. For example, clonesrepresenting segment “1” are placed in sub-array 504, but not in thesame sub-array as clones representing segment “2,” which, because it isadjacent on the natural chromosome, is placed in sub-array 506 instead.Segment “3,” which is adjacent to segment “2” on the natural chromosome,is represented by clones that are placed in sub-array 508 to avoidproximity to the clones for segment “2,” etc. An exemplary clonedistribution 500 may be redundantly repeated on several scale sizes, asdiscussed above. Thus, additional targets for clones representingsegments “1,” “5,” and “9” may be repeated in sub-array 510, andadditional targets for clones representing segments “2,” “6,” and “10”may be placed in sub-array 512, etc.

Thus, an exemplary array 202 implementation provides a comprehensivebattery of diverse tests that can be performed relatively inexpensivelycompared to costly separate conventional tests. Moreover, such anexemplary array 202 provides unprecedented accuracy, reliability, andconvenience for diagnosing a myriad of genetic alterations, for example,in one single CGH microarray test.

In one implementation, an arrangement motif for targets in sub-arraysmay include an orientation feature for positioning an array 202 duringtesting. This orientation feature may be a marking or design that can beimplemented by arranging the targets themselves, for example, bycreating a non-symmetric arrangement of the targets on the array 202 toform an arrow, or other directional indicator 504. The directionalindicator(s) 504 allow correct orientation of the array 202, e.g.,during insertion of the array 202 into a diagnostics engine 206. Theseorientation markings or design let a machine and/or human operatorrecognize an array's orientation.

High Availability Aspect

High availability (HA) is a term used between artisans in various tradesto refer to a system that is capable of providing reliable and/oraccurate service almost all of the time. Provision of reliable HAgenetic testing has been a longstanding problem. In one aspect of thesubject matter, the exemplary methods described herein achieve HAgenetic testing by creating very reliable components, by creatingelements that are fault tolerant, by creating relationships between theelements that avoid error, and by creating subsystems that are backed upby redundant provisioning. In an exemplary array 202, “redundantprovisioning” and “clustering” are design techniques that impart HA togenetic testing. Components within an exemplary array 202 or exemplarygenetic testing system (FIG. 2) are replicated so that the testingfunctions of the system are carried out simultaneously in differentparts, and if a subsystem—or a sub-array—fails, the test it performs iscarried out by a “spare.”

Thus, an exemplary array 202 constructed according to aspects of thesubject matter provides many high-availability features. Nucleic acidsequences used on an exemplary array 202 are selected to provide qualityinformation and diagnostic efficacy. Moreover, individual tests includedon an exemplary array 202 are repeated redundantly for quality assuranceand verification of test results. The placement of individual tests onan exemplary array 202 strategically eliminates many possibilities forhybridization errors and errors introduced by variations that occurwithin usual procedural tolerances.

Array Compression

FIG. 6 shows an exemplary method of producing a reduced size diagnosticarray 602. In one implementation, when arraying DNA targets (BAC clones,cDNA, oligonucleotides, etc.) on an array 602, the DNA targets from morethan one location on the genome 604 (2, 3, or more contiguous ornoncontiguous locations on the genome) are mixed and the mixture spottedas a single target on the array 602. This technique simplifies the array602 by reducing the number of targets that are arrayed on the array'ssolid support. For example, if an array contains 3,000 targets eachrepresenting a single BAC, the DNA from 3 contiguous (or noncontiguous)BACs can be pooled into a single tube, mixed, and spotted as a singletarget that contains a mixture of the 3 BACs. If this technique isperformed for every 3 BACs, then the same genetic contents (that arepresent on the aforementioned 3,000-target array) can be present in anarray 602 that has only 1,000 targets.

Exemplary Array Engine 200

FIG. 7 shows an exemplary implementation of an array engine 200, inwhich various components are communicatively coupled to design,implement, and/or construct an exemplary array 202. The components of anexemplary array engine 200 are logic modules or, may be combinations ofclinical processes, software, firmware, and/or hardware, and thus mayinclude components or processes that can be performed manually in someimplementations.

A selection engine 700 seeks to determine a set of chromosomal loci thathave reliable diagnostic efficacy—that is, chromosomal loci capable ofgenetic alteration indicative of disease and reliably readable forindicating either a presence or an absence of the genetic alteration. Alocus selector 702 included in the selection engine 700 may search orconsult one or more diagnostic loci databases 704 from which a clinicalrelevance evaluator 706 decides which loci are to be included in theexemplary array 202. The diagnostic loci databases 704 may take intoaccount population studies that help to determine the extent ofdeletion/duplication polymorphisms. For an exemplary array 202 that isto be used in a clinical application, diagnostic loci databases 704 thateliminate most latent polymorphisms allow the exemplary array 202 toavoid costly diagnostic procedures and counseling errors that resultfrom misdiagnosing benign polymorphisms as disease-causingabnormalities.

A FISH verifier 708 coupled with the selection engine 700 may be used toconfirm a base-pair sequence of a given locus, location of the sequencein the genome, or to test the diagnostic efficacy of a given locus priorto its inclusion in an exemplary array 202. More importantly, the FISHverifier 708 may also be used to reject clones from representing acertain segment of a locus. The rigorous assessment and screening ofbacterial artificial chromosomes (BACs) and other nuclei acid targetsand their use in an exemplary array is especially important when thearray 202 is used for clinical diagnosis.

A sequence coverage engine 710 coupled with the selection engine 700 mayassign multiple nucleic acid clones, each to represent a segment of abase-pair sequence of a chromosomal locus selected by the selectionengine 700. The sequence coverage engine 710 may further include asequence disassembler 712 to divide a base-pair sequence of achromosomal locus into proposed segments according to a schema. Forexample the disassembler 712 may break apart a base-pair sequence intopieces that have a certain length, polarity, etc., that facilitatesconstruction of the exemplary array 202 or the test procedures.

The sequence coverage engine 710 may include a segment assignment engine714 to divide a base-pair sequence of a chromosomal locus or achromosomal region associated with the locus into segments. The segmentassignment engine 714 determines the segmentation strategy and logic fora given locus. Sometimes the segment logic is determined by availabilityof a clone or oligonucleotide to represent the desired segment. Thus,the segment assignment engine 714 may consult one or more clonelibraries 720. In one implementation, the clone libraries 720 includelarge insert clones, capable of representing base-pair sequences, suchas bacterial artificial chromosomes (BACs), yeast artificial chromosomes(YACs), P1-derived artificial chromosomes (PACs), cosmids, plasmids,cDNAs, etc., and/or synthetic oligonucleotides.

The segment assignment engine 714 may also include a segment overlapengine 716 to implement a base-pair sequence overlap strategy for thesegments. Segment overlap can provide increased resolution and accuracyof test results, as overlapping portions of segments are, in a sense,tested twice, and because overlap results can be logically added orsubtracted to the underlying segment logic of the base-pair sequence ofa given chromosomal locus.

A clone assignor 718 may consult one or more clone libraries 720 toassociate a clone with each segment of the base-pair sequence of aselected chromosomal locus. Alternatively, a clone assignor 718 mayutilize services of a clone synthesizer 722 to create an oligomer ofnucleic acid to represent a segment, for example, using PCR or othermethods of nucleic acid synthesis and amplification.

A reference engine 724 may be communicatively coupled with the arrayengine 200 to incorporate additional base-pair sequences into targets ofan exemplary array 202 to provide reference controls for comparison withhybridization results from targets for the chromosomal loci.

The reference engine 724 may also include a regional context delimiter726 that further includes a telomeric sequence selector 728 and aperi-centromeric sequence selector 730 for selecting chromosomal regionsin the vicinity of one of the chromosomal loci. Often, in the case ofdeletion or duplication syndromes, it provides useful information totest the context or nearby genetic environment of the locus of interest.These regions may be assigned clones and added to target areas of anexemplary array 202. If a genetic condition being diagnosed is amicrodeletion syndrome, then the presence or absence of these regions inchromosomes of a patient being tested can be ascertained by theexemplary method to inform the diagnostician of the extent of a geneticdeletion. Thus, genetic regions (centromeric and telomeric) adjacent toa locus of interest may also be included in an exemplary array 202,e.g., to test the extent of a microdeletion.

The reference engine 724 may also include a flanking controls selector732. Clones that flank a clinically relevant locus can be selected andplaced at random on an exemplary array 202 as reference clones—i.e.,clones that are typically unaltered even in a patient that testspositive at the clinically relevant locus—thus providing a comparisonand a further assurance of quality. The reference clones can provide abaseline signal strength for comparison with an adjacent or nearbyclinically relevant locus when an exemplary array 202 is beingevaluated. Hence, the flanking controls selector 732 may consult one ormore reference sequence databases 734 to ascertain which additionalbase-pair sequences, if any, should be represented by clones andincorporated as flanking control targets to be logically associated witha chromosomal locus of interest, although not physically associated withthe chromosomal locus of interest on the array 202.

A distribution engine 736 may be included in an exemplary array engine200. An array generator 738 may be included in the distribution engine736 to design the geometry and size of the exemplary array 202 with itsvarious levels of sub-arrays. The geometry may depend on the number ofgenetic conditions being included for diagnosis; the number of segmentsused to represent each chromosomal locus associated with a geneticcondition; and the amount of redundancy to be built into the exemplaryarray 202.

A target isolation engine 740 logically distributes clones representingsegments that are adjacent on a native chromosome into non-adjacenttargets on the exemplary array 202. In other words, the target isolationengine 740 provides the measure of spatial isolation for clonesrepresenting adjacent segments of a chromosomal locus.

A redundancy engine 742 may be included in the distribution engine 736to cooperate with the array generator 738 in determining a geometry andsize for the exemplary array 202 and to determine a degree of redundancyof repeated target areas, repeated sub-arrays, and repeated arrangementmotifs of the targets and sub-arrays within an exemplary array 202. Thedegree of redundancy may be based on the degree of reliability desiredor the sensitivity and dependability of certain clones or certain testprocedures. A redundancy engine 742 may also impart a higher degree ofreliability and coverage to an exemplary array 202 by replicating theentire exemplary array 202 a certain number of times, for example, on asingle substrate. The amount of redundancy to be imparted can be relatedto the perceived diagnostic efficacy of the array 202 or part of thearray 202. The exemplary array engine 200 described above is one way ofproducing an exemplary diagnostic array 202.

Exemplary Diagnostics Engine 206

FIG. 8 shows an exemplary diagnostics engine 206 that exploits thefeatures of an exemplary array 202 produced by an exemplary array engine200 to yield genetic diagnoses that are more convenient, less expensive,more accurate, and more reliable than conventional diagnoses.

As with the exemplary array engine 200 described above, the variouscomponents of an exemplary diagnostics engine 206 are logic modules or,may be combinations of software, firmware, and/or hardware, and mayinclude components or processes that can be performed manually in someimplementations. In other words, the components of an exemplarydiagnostics engine 206 represent modules of logic or processes that canbe included in achieving precision genetic diagnoses using an exemplaryarray 202.

A target reader 802 is typically included in a diagnostics engine 206and of course may be a conventional part of a system that processes thekind of test selected for the exemplary array 202, for example, if theexemplary array 202 is a CGH microarray, then the target reader 802 canbe a conventional part of a CGH microarray analyzer.

A redundant target comparator 804 may be included in conjunction withthe target reader 802 to determine a test result for one type of cloneby comparing test results from multiple copies of the clone located inredundant targets across the exemplary array 202.

Array geometry 806 and target registration 808 may be included in thediagnostics engine 206. That is, the strategic placement of targets isstored in a memory or otherwise recorded and used to locate targets,especially redundantly replicated targets that have been isolated fromeach other. Alternatively, in some implementations the array geometryand placement of targets within the logical structure of the exemplaryarray 202 may be calculated according to a stored or built-in schema.

A locus reassembler 810 is communicatively coupled with the diagnosticsengine 206 to collate individual test results from the clonesrepresenting the segments of a locus. By collating test results fromindividual targets, the locus reassembler 810 obtains an overallcombined test result for the base-pair sequence of the entire locus.Thus, a locus reassembler 810 may include a segment collator 812 and anoverlap filter 814 to combine test results from individual targets toobtain or calculate a logical test result, such as a representativesignal, for the locus that the segments represent. If the correlationbetween a given target and its associated segment is not derivable by aschema, e.g., if there is no underlying order that can be derived bytarget registration 808, then the segment collator 812 may consult adatabase of segment assignments 816 (e.g., as generated by the arrayengine 200) to relate each target to a segment or to a controlreference, etc.

A baseline signal calibrator 818 may determine a signal thresholdagainst which positive and negative test results may be determined. Thebaseline signal calibrator 818 may take an average of at least some ofthe test results to calibrate an average signal strength. For example,in CGH, the strength of a fluorescence signal may be influenced by manyfactors, including the stringency of the test conditions, the quality ofthe equipment used to analyze results, etc. Additionally, the baselinesignal calibrator 818 may examine the signal strength of flankingcontrol references to determine the specific relative characteristics ofa typical positive or negative signal result for the test at hand.

A signal evaluator 820 receives a logically collated test result foreach locus and may compare the test result with the baseline signalobtained from the baseline signal calibrator 818. A flanking referencecomparator 822 may also be included to compare the test result for agiven locus with flanking control reference(s) added for comparison toan array 202. In modalities such as CGH, an evaluation that the testresult for a given locus is unremarkable or “normal” as opposed to anevaluation that the test result implies genetic alteration can usuallybe made either from the absolute strength of the signal, from acomparison with the baseline signal, and/or from a comparison with theflanking reference.

A genetic alterations database 824 may also be included to link anevaluation (that is, an evaluation that a particular locus possessesgenetic alteration) with a known genetic disease or condition.

Exemplary Methods

FIG. 9 shows an exemplary method 900 of selecting chromosomal loci. Inthe flow diagram, the operations are summarized in individual blocks.The method 900 may be performed by hardware, software, or combinationsof both, for example, by an exemplary selection engine 700 and othercomponents of an exemplary array engine 200.

At block 902, chromosomal loci are selected that are capable ofrepresenting a genetic alteration or genetic condition to be diagnosed.The selection aims to choose only loci with reliable diagnosticsignificance—that is, not only chromosomal loci at which geneticalteration is indicative of disease but also loci that are reliablyreadable for making a diagnosis. In some implementations, selection isautomated by selecting from a set of diagnostic loci databases 704 fromwhich a clinical relevance evaluator 706 decides which loci are to beincluded in an exemplary set. Selection can also be manual, resulting inhandpicked loci that represent a set of diseases and that demonstratediagnostic reliability.

At block 904, clinically irrelevant loci are discarded. A “whole genome”approach is abandoned as too imprecise for a clinical setting, costly infollow up of clinically irrelevant loci; and individual loci selectedabove at block 902 are eliminated from an exemplary array 202 if they donot test for a disease or yield other clinically relevant information.

At block 906, the base-pair sequence of each selected chromosomal locusis divided into segments. This may be accomplished by a segmentassignment engine 714 that implements segmentation. Thissequence-division logic may divide a base-pair sequence into segments,e.g., randomly; based on segment length; based on reactivity of thesegments; or again based on other factors, such as availability ofnucleic acid clones to represent the segments, etc. An overlap engine716 may implement logic to obtain segments whose adjacent ends cover thesame base-pairs of the sequence.

At block 908, a nucleic acid clone (or alternatively a syntheticoligonucleotide) is assigned to each segment. The assignment may beaccomplished by logic that links the base-pair sequence of a segment toan available clone from a clone library 720. Alternatively, a clonesynthesizer 722 may custom-produce an oligonucleotide to represent thebase-pair sequence of a segment. In one implementation, a large insertclone, such as a bacterial artificial chromosome (BAC), a yeastartificial chromosome (YAC), a P1-derived artificial chromosome (PAC), acosmid, a plasmid, or a cDNA is selected to represent the base-pairsequence of a segment.

At block 910, the mapping of each clone or oligonucleotide to itsrespective segment of the chromosomal locus is confirmed, for example,by a FISH verifier 708. Confirmation includes verifying that a givenclone uniquely maps to one segment and not to multiple segments, loci,or chromosomes. Confirmation may also include verifying the reliabilityof the mapping under various test conditions of variable stringency.

At block 912, clones that ineffectively map to a segment are discarded.A clone that demands, for proper mapping, test conditions that are toostringent or that are unique may fail the confirmation step as well asclones that do not map to the correct chromosomal locus, clones thathybridized to multiple loci in the genome, clones that cross-hybridizedto another chromosome, and clones that hybridized poorly under constantFISH conditions.

At block 914, clones that were discarded at block 912 are replaced bydifferent clones that map properly to respective chromosomal loci andthat can demonstrate proper mapping within the stringency tolerances oflikely test conditions. The logic of a clone assignor 718 may cooperatewith the logic of a segment assignment engine 714 in a “stair step”approach wherein either the segment assignment engine 714 first suggestsa proposed segment or alternatively, the clone assignor 718 firstsuggests a proposed known clone. A dialogue between the two logicmodules may ensue in which either can accept a proposal of the other orreject a proposal of the other and suggest an alternative. Proceedingback and forth in proposal-rejection-counterproposal dialogue, the twomodules arrive at an acceptable set of segments to represent achromosomal locus and a set of actual clones to represent the segments.

FIG. 10 shows an exemplary method 1000 of distributing clones on anexemplary array. In the flow diagram, the operations are summarized inindividual blocks. The method 1000 may be performed by hardware,software, or combinations of both, for example, by an exemplarydistribution engine 736 and other components of an exemplary arrayengine 200.

At block 1002, chromosomal loci are selected that are capable ofrepresenting a genetic alteration or genetic condition to be diagnosed.The selection aims, as at block 902, to choose only loci with reliablediagnostic efficacy—that is, not only chromosomal loci that are capableof genetic alteration indicative of disease but also loci that arereliably readable for making a diagnosis.

At block 1004, the base-pair sequence of each selected chromosomal locusis divided into segments, as above at block 906.

At block 1006, a nucleic acid clone or a synthetic oligonucleotide isassigned to each segment, as above at block 908.

At block 1008, the assigned clones (or oligonucleotides) are distributedon an exemplary array 202, for example, according to logic of adistribution engine 736. On an exemplary array 202, for a clone to avoidhybridization effects caused by an adjacent clone that represents asegment that is adjacent on a native chromosome, the clones areseparated, that is, placed in non-adjacent targets of an exemplary array202. Thus, for example, when the exemplary array 202 is exposed to testDNA and control DNA for CGH, inaccuracy and unreliability are notintroduced for a given array target by interference from hybridizationreactions that would occur if adjacent clones represented adjacentsequences on the native DNA.

FIG. 11 shows an exemplary method 1100 of flanking clinically relevantchromosomal loci with controls on an array. In the flow diagram, theoperations are summarized in individual blocks. The method 1100 may beperformed by hardware, software, or combinations of both, for example,by an exemplary reference engine 724 and other components of anexemplary array engine 200.

At block 1102, a chromosomal diagnostic locus is selected as ahybridization target. The locus is capable of genetic alterationindicative of a clinically relevant disease or condition.

At block 1104, a nucleic acid clone is placed on an array, such as anexemplary array 202, wherein the clone represents at least a segment ofthe selected locus. The clone may be placed more than once on an array,for example according to logic of a redundancy engine 742.

At block 1106, one or more flanking clones are selected as controls. Thecontrols comprise chromosomal sequences that remain unaltered regardlessof the genetic alteration being tested for at the chromosomal diagnosticlocus. That is, the control typically comprises a clone of chromosomalmaterial that maintains a constant base-pair sequence and dosage inindividuals who carry the genetic alteration being tested for at thechromosomal locus selected at block 1102. Such a flanking controlprovides a reference for comparing an array target against a controlsequence that was adjacent to the target on the chromosome. For example,in CGH, the reference target provides an intensity of a fluorescencesignal that should be present and unaltered in individuals who manifestthe genetic alteration at the chromosomal diagnostic locus of interest,and this reference signal is helpful because it is from a clone thatrepresents a sequence adjacent to the target on the native chromosome.

At block 1108, the flanking clones are randomly distributed across anexemplary array 202. Thus, without being affected by proximity to achromosomal diagnostic locus on an array 202, clones of sequences thatflank the diagnostic locus on the chromosome can be tested apart fromthe chromosomal locus for purposes of comparison and reference.

FIG. 12 shows an exemplary method 1200 of replicating an arrangementmotif for chromosomal loci on an array. In the flow diagram, theoperations are summarized in individual blocks. The method 1200 may beperformed by hardware, software, or combinations of both, for example,by an exemplary redundancy engine 742 and other components of anexemplary array engine 200.

At block 1202, a diagnostic efficacy of an arrangement motif forchromosomal loci in an array is determined. The arrangement motif may besimple, such as the motif of a single array target adjacently flanked bya single reference target, or may be more complex such as the layout ofan entire sub-array of an exemplary array 202, wherein targets thatrepresent adjacent segments of a native chromosome are placednon-contiguously on the exemplary array 202. Then too, an exemplarymotif may be the arrangement of only those clones that representsegments of a single chromosomal locus. Yet again, an exemplaryarrangement motif may be multiple small-scale arrangement motifs withina larger-scale arrangement motif, for example, an exemplary array 202containing multiple repeating sub-arrays that is itself capable of beingredundantly repeated on an even larger substrate. The diagnosticefficacy of one or more of these arrangement motifs may be determinedtheoretically or actually. The more reliable the motif for yieldingdiagnostic results, the fewer times the motif may need to be redundantlyrepeated via this exemplary method 1200.

Thus, at block 1204 the arrangement motif is replicated on an exemplaryarray 202 multiple times. An arrangement motif that is useful but notvery dependable or that is not very forgiving of less than stringenttest conditions may be replicated many times on an exemplary array 202.Conversely, a very dependable motif may be replicated only a few timesor included only in its original form in order to conserve resources.

In one implementation, replicating an arrangement motif may includecreating an orientation marking or design for positioning an array 202during testing. The orientation marking(s) or design may be implementedby arranging the targets themselves, for example, by creating anon-symmetric arrangement of the targets on the array 202 to form anarrow, or other directional indicator. The directional indicator(s)allow correct orientation of the array 202, e.g., during insertion ofthe array 202 into a diagnostics engine 206. These orientation markingsor design let a machine and/or human operator recognize an array'sorientation.

At block 1206, an array implementation that includes ample targets totest for each genetic alteration once may itself be replicated a numberof times in inverse proportion to the determined or hypothesizeddiagnostic efficacy of the array as a whole or a part of the array—evena single target. In one implementation, the amount of redundancyimparted to an exemplary array 202 derives from the least dependableelement of the array.

Exemplary Implementation

In one implementation, the diagnostic loci databases 704 of the arrayengine 200 included genome resources, such as a Marshfield Genetic Map(Marshfield Clinic, Marshfield, Wis.). Selection engine logic 700 choseclinically relevant chromosomal loci for potential clone assignment fromloci known to be involved in dosage imbalances that result in clinicallyrelevant diseases, including known microdeletion syndromes, knownmicroduplication syndromes, and terminal deletion syndromes, as shown inTable 1:

TABLE 1 CLINICALLY RELEVANT MICORODELETION AND MICRODUPLICATION LOCIDisorder Locus Location MONOSOMY 1P MULTIPLE 1P36 HOLOPROSENCEPHALY 2SIX3 2P21 NEPHRONOPHTHISIS NPHP1 2Q13 HOLOPROSENCEPHALY 6 MULTIPLE 2Q371-27.3 WOLF-HIRSCHHORN MULTIPLE 4P16 CRI-DU-CHAT MULTIPLE 5P15 CORNELIADE LANGE NIPBL 5P13 SAETHRE-CHOTZEN TWIST 7P21 GREIG GL13 7P13CEPHALOPOLYSYNDACTYLY WILLIAMS SYNDROME ELN 7Q11.23 HOLOPROSENCEPHALY 3SHH 7Q36 CHARGE SYNDROME CHD7 8Q12.1 LANGER-GIEDION EXT1 8Q24TRICHORHINOPHALANGEAL TRPS1 8Q24 SYNDROME HOLOPROSENCEPHALY 7 PATCH9Q22.3 DIGEORGE SYNDROME II MULTIPLE 10P13 BECKWITH-WIEDEMANN IGF211P15.5 WAGR SYNDROME WNT, PAX6 11P13 POTOCKI-SHAFFER SYNDROME EXT2,ALX4 11P11.2 NOONAN SYNDROME PRPN11 12Q24.1 RETINOBLASTOMA/MR RB1 13Q14HOLOPROSENCEPHALY 5 ZIC2 13Q32 PRADER-WILLI SYNDROME SNRPN 15Q12ANGELMAN SYNDROME UBE3A 15Q12 RUBINSTEIN-TAYBI CREBBP 16P13.3 TUBEROUSSCLEROSIS TSC2 16P13.3 POLYCYSTIC KIDNEY DISEASE PKD1 16P13.3MILLER-DIEKER SYNDROME LIS1 17P13.3 CHARCOT-MARIE-TOOTH PMP22 17P12DISEASE SMITH-MAGENIS SYNDROME RAI1 17P11.2 DUPLICATION PROXIMAL 17MULTIPLE 17P11.2 NEUROFIBROMATOSIS I NF1 17Q11.2 HOLOPROSENCEPHALY 4TGIF 18P11.3 ALAGILLE SYNDROME JAG1 20P11.23 HOLOPROSENCEPHALY 1TMEM1/EHOC1 21Q22.3 DIGEORGE SYNDROME I TUPLE1/TBX1 22Q11.2 STEROIDSULFATASE DEFICIENCY STS XP22.3 MICROPHTHALMIA WITH LINEAR MULTIPLEXP22.3 SKIN DEFECTS GLYCEROL KINASE DEFICIENCY GK XP21 ADRENALHYPOPLASIA DAX1 XP21 CONGENITA DUCHENNE MUSCULAR DYSTROPHIN XP21DYSTROPHY PELIZAEUS-MERZBACHER PLP1 XQ21 DISEASE X-LINKED HETEROTAXYZIC3 XQ26.2 SEX DETERMINING FACTOR SRY YP11.3

Pericentromeric and telomeric loci were also selected. These loci wereuniquely selected to identify aneuploidy (extra or missing chromosomes),deletions or duplications of the telomeric regions, deletions orduplications of the pericentromeric regions, marker chromosomes, andunbalanced derivative chromosomes, as shown below in TABLE 2:

TABLE 2 PERICENTROMERIC AND TELOMERIC LOCI Chromosome Region 1P36.3 1P121Q21 1Q44 2P25.3 2P11.2 2Q11.2 2Q37.3 3P26.3 3P11.2 3Q11.2 3Q29 4P16.34P12 4Q12 4Q35.2 5P15.3 5P12 5Q11.2 5Q35.3 6P25.3 6P11.2 6Q12 6Q277P22.3 7P11.2 7Q11.21 7Q36.3 8P23.3 8P11.2 8Q11.2 8Q24.3 9P24.3 9P11.29Q13 9Q34.3 10P15.3 10P11.21 10Q11.21 10Q26.3 11P15.5 11P11.2 11Q1211Q25 12P13.33 12P11.21 12Q12 12Q24.33 13Q12.11 13Q34 14Q11.2 14Q32.3315Q11.2 15Q26.3 16P13.3 16P11.2 16Q21.1 16Q24.3 17P13.3 17P11.2 17Q11.217Q 18P11.32 18P11.21 18Q11.2 18Q23 19P13.3 19P12 19Q12 19Q13.43 20P1320P11.21 20Q11.21 20Q13.33 21Q11.2 21Q22.3 22Q11.2 22Q13.3 XP22.3XP11.22 XQ11.2 XQ28 YP22.3 YP11.3 YP11.2 YQ11.2

For this implementation, locus selection was influenced by availabilityof clones in the clone libraries 720. A group of approximatelynine-hundred BAC clones were considered for representation of theclinically relevant chromosomal loci. A FISH verifier 708 revealed thatapproximately 7% of the clones were mismapped based on map locationsobtained from two publicly available databases (some mapped to the wrongchromosome and some mapped to a different locus on the same chromosome),approximately 17% cross-hybridized to other chromosomes, andapproximately 10% either did not hybridize or showed poor hybridizationsignals under uniform FISH conditions). Thus, only about 65% of clonesmet selection criteria as applied, for example, by the FISH verifier708. These selected clones were placed into an exemplary array 202.

The clone assignor 718 identified large-insert clones, mostly BACs, torepresent the selected loci, searching by gene, STS marker, or byprevious publication of a clone in a clone library 720 to anchor eachchromosomal locus of interest.

The segment assignment engine 714 developed a contiguous segmentstrategy to cover each locus of interest. A minimum of three overlappingclones was selected to cover segments of each locus to be represented onthe exemplary array 202. A FISH verifier 708, employing uniformexperimental conditions on a single control male whose genetic materialwas used throughout this trial, confirmed that each clone mappedproperly to its respective chromosomal locus. The FISH verifier 708rejected clones that did not map to the correct chromosomal locus,clones that hybridized to multiple loci in the genome, clones thatcross-hybridized to another chromosome, and clones that hybridizedpoorly under these constant FISH conditions.

Segment assignment engine 714 replaced the rejected clones with BACsthat properly map to respective chromosomal loci as suggested by thediagnostic loci databases 704 and as confirmed by the FISH verifier 708.

At known microdeletion and microduplication loci in which structuralrearrangements are mediated by low copy repeat (LCR) regions that flankthe deleted or duplicated locus, a telomeric sequence selector 728 and acentromeric sequence selector 730 of the reference engine 724 selected“control” BAC contigs outside the LCR regions, adjacent on either sideof the locus. No BACs that map to the LCRs were selected.

Array design logic in accordance with the array generator 738, thetarget isolation engine 740, and the redundancy engine 742 of thedistribution engine 736 was implemented to construct the exemplary array202. To ensure that no particular area of the exemplary array 202 wouldcause deletion misclassifications because of naturally contiguous clonesadjacent to each other on the exemplary array 202, distribution logic ofthe target isolation engine 740 placed each clone selectively in a384-well plate (c.f., FIG. 5). The redundancy engine 742 called forprinting the plate four times on the exemplary array 202.

Implementation details include insert-DNA extraction with a RPM SPINMIDI KIT followed by sonicating 5 μg of probe DNA to a final sizebetween 500 bp-20 kb (Q-BIOgene, Carlsbad, Calif., USA). The DNA wasprecipitated with NaAc 3M pH 5.2 (1:8 of the total volume) andisopropanol (1:1 volume). The DNA was hydrated with sterile water to afinal concentration of 625 ng/μl. Before printing the exemplary array202, 50% DMSO was added with nitrocellulose as has been previouslydescribed.

Array printing was conducted with an OMNIGRID ACCENT MACHINE(GeneMachine, San Carlos, Calif., USA) at 30% humidity and a temperatureof 24° C. using low-autofluorescence slides (VWR International, WestChester, Pa., USA) treated with aminosilane (Sigma-Aldrich, SheboyganFalls, Wis., USA). Printed slides were baked at 80° C. from 4 hours toovernight and then washed with 80° C. millipore water for 2 minutes andcold ethanol of 95% for 1 minute. Blocking of the slides was achievedwith 10% bovine serum albumin fraction V (Sigma, St. Louis, Mo., USA)and 20 μg salmon sperm DNA (Invitrogen, Carlsbad, Calif., USA) in ahumid chamber at 45° for 2 hours. Slides were denatured in boilingmillipore water, then dehydrated with 95% ethanol at −20° C. and storedin a desiccator.

Genomic DNA was extracted with a PUREGENE DNA ISOLATION KIT fromlymphoblastoid cell lines, peripheral blood, or cultured tissues of thesubjects and phenotypically normal male and female references (GentraSystems, Inc. Minneapolis, Minn., USA). Genomic DNA was digested withDpn II (New England Biolabs, Inc., Beverly, Mass., USA) andreprecipitated (1:8 volume of NaAc 3M pH5.2 and 1:1 volume ofisopropanol).

In one implementation, a dye-reversal strategy was used on two separateexemplary arrays 202 in which 500 ng of both subject and reference DNAswere labeled (BIO PRIME DNA LABELING SYSTEM, Invitrogen) with Cyanine3(Cy3) and Cyanine5 (Cy5), respectively.

The subject and reference DNA were co-hybridized to a first exemplaryarray 202 and then oppositely labeled and co-hybridized to a secondexemplary array 202. Shortly after the labeling, probes were purifiedwith MICROCON filter units (Millipore, Billerica, Mass., USA), and ˜500ng of subjects' DNA, combined with an equal amount of reverse-sexcontrol DNA, was co-precipitated with 50 μg of Cot1-DNA (Invitrogen) andhydrated with 15.5 μl ULTRAHYB (Ambion, Austin, Tex., USA). The labeledgenomic DNAs were denatured at 72° C. for 5 minutes, preannealedimmediately after at 37° C. for 1 hour, placed onto an exemplary array202, and covered with a 22×22 mm coverslip.

For the test 204, hybridization was performed in an incubation chamber(Corning Incorporated Life Sciences, Acton, Mass., USA) at 37° C. withshaking for 14-16 hours. Following the hybridization, the coverslipswere removed with 1×PBS and the exemplary arrays 202 were washed with50% formamide+2×SSC+0.1% SDS at 45° C. for 20 minutes and 1×PBS for 20minutes at room temperature in the dark. The exemplary arrays 202 werethen rinsed with 0.2×SSC and millipore water and dried immediately.

A target reader 802 comprising in part a GENEPIX 4000B dual-laserscanner and individual spots were analyzed with GENEPIX PRO 4.0 imagingsoftware (Axon Instruments, Union City, Calif., USA). Two simultaneousscans of each array were obtained at wavelengths of 635 nm and 532 nm.The average ratios of four spots for each subject were analyzed withACUITY 3.0 software (Axon Instruments, Union City, Calif., USA).Thresholds for copy-number gain and loss were set at 1.5 and 0.5,respectively. After subtraction of background noise, the ratio offluorescence intensities derived from hybridized test and control DNAwas calculated and normalized by the ratios measured from referencetargets on the same slide. These reference targets always contained DNAthat was of the same complexity as the target spots of the selectedchromosomal loci of interest.

Results were verified using FISH. More specifically, DNA was extractedfrom BAC clones using a standard alkaline lysis protocol and labeled bynick translation with biotin-dUTP or digoxigenin-dUTP (Roche Diagnostic,Indianapolis, Ind., USA). The probes were denatured at 70° C. for 10minutes and hybridized to denatured metaphase chromosomes on microscopeslides at 37° C. The following day the slides were washed with 50%formamide at 42° C. for 15 minutes, 2×SSC at 37° C. for 8 minutes, and1×PBD at room temperature for 2 minutes. The signals were amplified withFITC-avidin (Sigma) and anti-avidin (Sigma) to detect the biotin-dUTP,and with anti-digoxigenin monoclonal antibody, anti-mouseIgG-digoxigenin and anti-digoxigenin-rhodamine FAB fragments (Sigma) todetect the dig-dUTP. The slides were counterstained with DAPI. Cellswere examined with a ZEISS AXIOPLAN II fluorescence microscope equippedwith a triple-bandpass filter that allows multiple colors to bevisualized simultaneously. Digital images were captured and stored withISIS software V 3.4.0 (Metasystems, Altlussheim, Germany).

Exemplary Results

The exemplary array 202 identified deletion and duplicationpolymorphisms in the phenotypically normal individuals and detected allof the expected chromosomal alterations in the patients with knownabnormalities. In addition, previously undetected clinically relevantabnormalities were revealed by the exemplary array 202. Theabnormalities detected by the exemplary array 202 were confirmed viaFISH as described above.

A previously undetected terminal deletion of 14q was identified by theexemplary array 202 in an individual who was studied previously withtelomere FISH analysis. This deletion was subsequently confirmed byFISH. In general, the exemplary array 202 allowed accurate and reliabledetection of deletions (1:2/dosage difference) and duplications (2:3dosage difference).

In one implementation, an exemplary array 202 identified a smallduplicated segment of 1p36 (˜750 kb) that could not be detected usingconventional mapping techniques. The exemplary array 202 provedinvaluable for detecting this cryptic complex rearrangement.

An exemplary array 202 was also useful in detecting gene dosagedifferences and in the detection of female carriers of deletions on theX chromosome. The exemplary array 202 was particularly useful inidentifying female carriers of Duchenne muscular dystrophy (DMD)deletions.

CONCLUSION

The subject matter described above can be implemented as logic modules,methods, clinical processes, diagnostic array articles, hardware,software, and various combinations of each of these. In certainimplementations, the subject matter may be described at least in part inthe general context of computer-executable instructions, such as programmodules, being executed by a computing device or communications device.Generally, program modules include routines, programs, objects,components, data structures, etc. that perform particular tasks orimplement particular abstract data types.

The foregoing discussion describes exemplary methods and apparatuses forachieving precision genetic diagnoses. Although the subject matter hasbeen described in language specific to structural features and/ormethodological acts, it is to be understood that the subject matterdefined in the appended claims is not necessarily limited to thespecific features or acts described above. Rather, the specific featuresand acts described above are disclosed as example forms of implementingthe claims.

1. A method for precision genetic diagnosis, comprising: selecting alocus associated with a genetic condition to be diagnosed; representingat least part of a base-pair sequence of the locus as multiple base-pairsegments; selecting a reference base-pair sequence unrelated to thegenetic condition; assigning one of clones or oligomers to represent themultiple base-pair segments and the reference base-pair sequence;arranging the clones or oligomers representing the multiple base-pairsegments on a microarray for a comparative genomic hybridization (CGH)test; and arranging the clones or oligomers representing the referencebase-pair sequence on the microarray for a CGH test.
 2. The method ofclaim 1, further comprising comparing the CGH test of the referencebase-pair sequence with the CGH test of the base-pair segments todetermine a degree of genetic alteration of the locus for diagnosing thegenetic condition.
 3. The method of claim 1, further comprisingarranging the clones or oligomers in separate locations on themicroarray to avoid hybridization influences.
 4. The method of claim 1,wherein the reference base-pair sequence occurs in proximity to thelocus on a chromosome.
 5. The method of claim 1, wherein the referencebase-pair sequence occurs adjacent to the locus on a chromosome.
 6. Themethod of claim 5, further comprising flanking the clones or oligomersrepresenting the base-pair segments of the locus on the microarray withthe clones or oligomer representing the reference base-pair sequenceadjacent to the locus on the chromosome.
 7. A method for precisiongenetic diagnosis, comprising: selecting a chromosomal locus associatedwith a genetic condition to be diagnosed; representing at least part ofthe base-pair sequence of the chromosomal locus in one or more targetareas of a comparative genomic hybridization array; and flanking one ormore of the target areas with one or more reference target areas thatinclude one or more reference base-pair sequences that are unalteredwith respect to the genetic condition to be diagnosed; and wherein afluorescence signal from the reference base sequence is capable of beingcompared with a fluorescence signal from the one or more target areasrepresenting the chromosomal locus.
 8. The method as recited in claim 7,wherein at least one of the reference base-pair sequences is contiguouswith the chromosomal locus in vivo.
 9. A method, comprising: selecting achromosomal locus associated with a genetic condition to be diagnosed;representing at least part of the base-pair sequence of the chromosomallocus in one or more target areas of a comparative genomic hybridizationarray; and representing, in target areas of the comparative genomichybridization array, a chromosomal region in the vicinity of thechromosomal locus in vivo, wherein an extent of a base-pair sequencedeletion associated with the chromosomal locus is capable of beingdetermined from comparative genomic hybridization of the chromosomalregion.
 10. The method of claim 9, wherein the chromosomal locuscomprises one of 1p36.3, 1p12, 1q21, 1q44, 2p25.3, 2p11.2, 2q11.2,2q37.3, 3p26.3, 3p11.2, 3q11.2, 3q29, 4p16.3, 4p12, 4q12, 4q35.2,5p15.3, 5p12, 5q11.2, 5q35.3, 6p25.3, 6p11.2, 6q12, 6q27, 7p22.3,7p11.2, 7q11.21, 7q36.3, 8p23.3, 8p11.2, 8q11.2, 8q24.3, 9p24.3, 9p11.2,9q13, 9q34.3, 10p15.3, 10p11.21, 10q11.21, 10q26.3, 11p15.5, 11p11.2,11q12, 11q25, 11p13.33, 12p11.21, 12q12, 12q24.33, 13q12.11, 13q34,14q11.2, 14q32.33, 15q11.2, 15q26.3, 16p13.3, 16p11.2, 16q21.1, 16q24.3,17p13.3, 17q11.2, 18p11.32, 18p11.21, 18q11.2, 18q23, 19p13.3, 19p12,19q12, 19q13.43, 20p13, 20p11.21, 20q11.21, 20q13.33, 21q11.2, 21q22.3,22q11.2, 22q13.3, Xp22.3, Xp11.22, Xq11.2, Xq28, YP11.3, Yp11.2, andYQ11.2; and wherein the respective chromosomal region is respectively inthe vicinity of the corresponding chromosomal locus in vivo.